Abstract: Building on a Lucas-tree asset pricing model, this paper relates the tail risk of asset prices to the component-density of a Normal-Laplace mixture distribution and proposes a new method to measure extreme event behavior in financial markets. The hidden state of the model represents the underlying state of the macroeconomy, which follows a two-state Markov regime switching process. Conditional on the state being ``normal''
or ``extreme'', the log dividend is subject to Normal or Laplace (fat-tailed) shocks respectively. The asset's price is derived from discounted dividend values, where the stochastic discount factor is determined by the utilility maximization of a representative agent holding the asset. Finally, identifiability of the model parameters, Maximum Likelihood estimation techniques and asymptotic properties of MLE are discussed, and the estimation results are illustrated using S&P index returns.

Abstract: We present a rational expectation equilibrium with
asymmetric information and heterogeneous investors. In a Bayesian
framework, agents update their information based on their private
information and market price of securities. By assuming that home
investors have a cumulative information advantage over foreign
investors, the home bias in international portfolio holdings is
investigated.

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